The Problem:

After selecting and installing a product, administrative staff found themselves "inundated with data" and found that it was humanly impossible to interpret or analyze it all.

The Solution:

The customer's team did more research and then tested multiple possible solutions. They settled on on Netuitive’s self-learning performance management technology.

The customer said “Netuitive is the only vendor that had the advanced predictive analytics for IT for what we were trying to do. It complements our APM solution very well and can give very accurate, advanced warning of impending application performance issues.” After going into production, Netuitive's software proved itself immediately.

Before implementing Netuitive with the APM software, the company was experiencing 600 alerts per day from one of the critical applications. After implementing Netuitive, the alerts dropped to 60 actionable alerts per week. An improvement in accuracy of 99% for performance alerts.

Snapshot analysis

The key take away points are that many distributed workloads, regardless of whether they're executing on physical or virtual server or whether they're running locally or somewhere in the clouds, have become too complex for administrators to manage in real time. In this case, adding self-learning analytical technology to the mix reduced false alerts by 99%.

Although this is a single use case, it is clear that some sort of analytical management solution is very likely to be needed when organizations deploy highly distributed, critical workloads. Netuitive is one of the many competitors to offer such tools. Of all of the competitors I've had the opportunity to speak with, Netuitive appears to be the only one offering a self-learning capability. This should make the product easier to use over the long haul.

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